MultRegCMP: Bayesian Multivariate Conway-Maxwell-Poisson Regression Model for Correlated Count Data

Fits a Bayesian Regression Model for multivariate count data. This model assumes that the data is distributed according to the Conway-Maxwell-Poisson distribution, and for each response variable it is associate different covariates. This model allows to account for correlations between the counts by using latent effects based on the Chib and Winkelmann (2001) <http://www.jstor.org/stable/1392277> proposal.

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: purrr, mvnfast, stats, progress, bayesplot, ggplot2, cowplot
Published: 2024-06-20
DOI: 10.32614/CRAN.package.MultRegCMP
Author: Mauro Florez [aut, cre]
Maintainer: Mauro Florez <mf53 at rice.edu>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: MultRegCMP results

Documentation:

Reference manual: MultRegCMP.pdf

Downloads:

Package source: MultRegCMP_0.1.0.tar.gz
Windows binaries: r-devel: MultRegCMP_0.1.0.zip, r-release: MultRegCMP_0.1.0.zip, r-oldrel: MultRegCMP_0.1.0.zip
macOS binaries: r-release (arm64): MultRegCMP_0.1.0.tgz, r-oldrel (arm64): MultRegCMP_0.1.0.tgz, r-release (x86_64): MultRegCMP_0.1.0.tgz, r-oldrel (x86_64): MultRegCMP_0.1.0.tgz

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